Image sharpening and contrast enhancement are important components of signal processing, including image and video-signal processing. One currently available technique for sharpening, referred to as “unsharp masking,” involves convolution of an original signal with a filter, subtraction of the resulting filtered image from the input image to produce a correction signal, multiplication of the correction signal by an amplification factor, and addition of the amplified correction signal to the original signal to produce an enhanced image. However, unsharp masking can have unfortunate side effects including amplifying noise within the original image and a need for tedious, empirical parameter adjustment in order to ameliorate introduction, by unsharp masking, of different types of artifacts, including halos around objects within the image and feature reflections. For these reasons, researchers and developers of signal processing methods and systems, as well as vendors of signal-processing methods and systems and vendors of various products, instruments, and devices that employ signal processing, have recognized the need for better, computationally efficient sharpening and contrast-enhancement methods and systems that minimize noise amplification and artifact introduction.